Identification of novel spinal cholinergic genetic subtypes disclose <i>Chodl</i> and <i>Pitx2</i> as markers for fast motor neurons and partition cells
Bibliographic record
Abstract
Spinal cholinergic neurons are critical for motor function in both the autonomic and somatic nervous systems and are affected in spinal cord injury and in diseases such as amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy. Using two screening approaches and in situ hybridization, we identified 159 genes expressed in typical cholinergic patterns in the spinal cord. These include two general cholinergic neuron markers, one gene exclusively expressed in motor neurons, and nine genes expressed in unknown subtypes of somatic motor neurons. Further, we present evidence that chondrolectin (Chodl) is expressed by fast motor neurons and that estrogen-related receptor beta (ERRbeta) is a candidate marker for slow motor neurons. In addition, we suggest paired-like homeodomain transcription factor 2 (Pitx2) as a marker for cholinergic partition cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".